[Fonction de l'ARNnc exosomal HEIH dans le carcinome hépatocellulaire associé au virus de l'hépatite B]. / Function of exosomal lncRNA-HEIH in hepatocellular carcinoma associated with hepatitis B virus.

Long non-coding RNA-HEIH (lncRNA-HEIH) is a potential biomarker for patients with hepatocellular carcinoma (HCC), but exosomal lncRNA-HEIH in patients with hepatitis B virus-associated HCC (B-HCC) is unclear. This study aimed to investigate the expression of exosomal lncRNA-HEIH in B-HCC patients and explore its clinical significance. We collected blood samples from 60 B-HCC patients, 60 non-hepatitis virus-associated HCC (N-HCC) patients, and 50 healthy volunteers. Exosomal lncRNA-HEIH levels were measured by real-time PCR and analyzed for their correlation with patient prognosis using Kaplan-Meier analysis. Multivariate COX regression analysis was conducted to identify factors affecting patient outcomes. The effects of lncRNA-HEIH on carcinogenesis were also investigated by constructing a Huh7 cell line stably expressing the hepatitis B virus. In the B-HCC group, there was a positive correlation between hepatitis B virus and exosomal lncRNA-HEIH. The 5-year survival rate of the exosomal lncRNA-HEIH high-expression group was significantly lower than that of the low-expression group in the B-HCC group, but not in the N-HCC group. Exosomal lncRNA-HEIH level was related to the TNM stage, lymph node metastasis and AFP. Exosomal lncRNA-HEIH level was independent risk factors for poor prognosis in B-HCC patients. In Huh7-HBV cells, lncRNA-HEIH level was significantly higher than in control, and the migration capacity of Huh7-HBV cells decreased significantly after down-regulating lncRNA-HEIH. Our findings suggest that exosomal lncRNA-HEIH is abnormally expressed and closely related to poor prognosis in B-HCC patients, indicating its potential as a diagnostic and therapeutic target for HBV-associated HCC.

TIN2-mediated reduction of mitophagy induces RPE senescence under high glucose.

The telomere-associated protein TIN2 localizes to both telomeres and mitochondria. Nevertheless, the impact of TIN2 on retinal pigment epithelial (RPE) cells in diabetic retinopathy (DR) remains unclear. This research aims to examine the role of TIN2 in the senescence of RPE and its potential as a therapeutic target. Western blotting and immunofluorescence staining were utilized to identify TIN2 expression and mitophagy. RT-qPCR was employed to identify senescent associated secretory phenotype (SASP) in ARPE-19 cells infected with TIN2 overexpression. To examine mitochondria and the cellular senescence of RPE, TEM, SA-ß-gal staining, and cell cycle analysis were used. The impact of TIN2 was examined using OCT and immunohistochemistry in mice. DHE staining and ZO-1 immunofluorescence were applied to detect RPE oxidative stress and tight junctions. Our research revealed that increased mitochondria-localized TIN2 aggravated the cellular senescence of RPE cells both in vivo and in vitro under hyperglycemia. TIN2 overexpression stimulated the mTOR signaling pathway in ARPE-19 cells and exacerbated the inhibition of mitophagy levels under high glucose, which can be remedied through the mTOR inhibitor, rapamycin. Knockdown of TIN2 significantly reduced senescence and mitochondrial oxidative stress in ARPE-19 cells under high glucose and restored retinal thickness and RPE cell tight junctions in DR mice. Our study indicates that increased mitochondria-localized TIN2 induced cellular senescence in RPE via compromised mitophagy and activated mTOR signaling. These results propose that targeting TIN2 could potentially serve as a therapeutic strategy in the treatment of DR.

Inhibition of Drp1- Fis1 interaction alleviates aberrant mitochondrial fragmentation and acute kidney injury.

BACKGROUND: Acute kidney injury (AKI) is a common clinical disorder with complex etiology and poor prognosis, and currently lacks specific and effective treatment options. Mitochondrial dynamics dysfunction is a prominent feature in AKI, and modulation of mitochondrial morphology may serve as a potential therapeutic approach for AKI. METHODS: We induced ischemia-reperfusion injury (IRI) in mice (bilateral) and Bama pigs (unilateral) by occluding the renal arteries. ATP depletion and recovery (ATP-DR) was performed on proximal renal tubular cells to simulate in vitro IRI. Renal function was evaluated using creatinine and urea nitrogen levels, while renal structural damage was assessed through histopathological staining. The role of Drp1 was investigated using immunoblotting, immunohistochemistry, immunofluorescence, and immunoprecipitation techniques. Mitochondrial morphology was evaluated using confocal microscopy. RESULTS: Renal IRI induced significant mitochondrial fragmentation, accompanied by Dynamin-related protein 1 (Drp1) translocation to the mitochondria and Drp1 phosphorylation at Ser616 in the early stages (30 min after reperfusion), when there was no apparent structural damage to the kidney. The use of the Drp1 inhibitor P110 significantly improved kidney function and structural damage. P110 reduced Drp1 mitochondrial translocation, disrupted the interaction between Drp1 and Fis1, without affecting the binding of Drp1 to other mitochondrial receptors such as MFF and Mid51. High-dose administration had no apparent toxic side effects. Furthermore, ATP-DR induced mitochondrial fission in renal tubular cells, accompanied by a decrease in mitochondrial membrane potential and an increase in the translocation of the pro-apoptotic protein Bax. This process facilitated the release of dsDNA, triggering the activation of the cGAS-STING pathway and promoting inflammation. P110 attenuated mitochondrial fission, suppressed Bax mitochondrial translocation, prevented dsDNA release, and reduced the activation of the cGAS-STING pathway. Furthermore, these protective effects of P110 were also observed renal IRI model in the Bama pig and folic acid-induced nephropathy in mice. CONCLUSIONS: Dysfunction of mitochondrial dynamics mediated by Drp1 contributes to renal IRI. The specific inhibitor of Drp1, P110, demonstrated protective effects in both in vivo and in vitro models of AKI.

BNST GABAergic neurons modulate wakefulness over sleep and anesthesia.

The neural circuits underlying sleep-wakefulness and general anesthesia have not been fully investigated. The GABAergic neurons in the bed nucleus of the stria terminalis (BNST) play a critical role in stress and fear that relied on heightened arousal. Nevertheless, it remains unclear whether BNST GABAergic neurons are involved in the regulation of sleep-wakefulness and anesthesia. Here, using in vivo fiber photometry combined with electroencephalography, electromyography, and video recordings, we found that BNST GABAergic neurons exhibited arousal-state-dependent alterations, with high activities in both wakefulness and rapid-eye movement sleep, but suppressed during anesthesia. Optogenetic activation of these neurons could initiate and maintain wakefulness, and even induce arousal from anesthesia. However, chronic lesion of BNST GABAergic neurons altered spontaneous sleep-wakefulness architecture during the dark phase, but not induction and emergence from anesthesia. Furthermore, we also discovered that the BNST-ventral tegmental area pathway might participate in promoting wakefulness and reanimation from steady-state anesthesia. Collectively, our study explores new elements in neural circuit mechanisms underlying sleep-wakefulness and anesthesia, which may contribute to a more comprehensive understanding of consciousness and the development of innovative anesthetics.

A direct electrochemical sensor based on covalent organic frameworks/platinum nanoparticles for the detection of ofloxacin in water.

A direct electrochemical sensor based on covalent organic frameworks (COFs)/platinum nanoparticles (PtNPs) composite was fabricated for the detection of ofloxacin (OFX) in water. Firstly, the COF material was synthesized via the condensation reaction of 1,3,5-tris(4-aminophenyl)benzene (TAPB) with terephthalaldehyde (TPA) and integrated with PtNPs by in situ reduction. Then, TAPB-TPA-COFs/PtNPs composite was loaded onto the surface of the glassy carbon electrode (GCE) by drip coating to construct the working electrode (TAPB-TPA-COFs/PtNPs/GCE). The electrochemical performance of TAPB-TPA-COFs/PtNPs/GCE showed a significant improvement compared with that of TAPB-TPA-COFs/GCE, leading to a 3.2-fold increase in the electrochemical signal for 0.01 mM OFX. Under optimal conditions, the TAPB-TPA-COFs/PtNPs/GCE exhibited a wide linear range of 9.901 × 10-3-1.406 µM and 2.024-15.19 µM with a detection limit of 2.184 × 10-3 µM. The TAPB-TPA-COFs/PtNPs/GCE-based electrochemical sensor with excellent performance provides great potential for the rapid and trace detection of residual OFX.

Prediction of Gleason score in prostate cancer patients based on radiomic features of transrectal ultrasound images.

OBJECTIVES: The aim of this study was to develop a model for predicting the Gleason score of patients with prostate cancer based on ultrasound images. METHODS: Transrectal ultrasound images of 838 prostate cancer patients from The Cancer Imaging Archive database were included in this cross-section study. Data were randomly divided into the training set and testing set (ratio 7:3). A total of 103 radiomic features were extracted from the ultrasound image. Lasso regression was used to select radiomic features. Random forest and broad learning system (BLS) methods were utilized to develop the model. The area under the curve (AUC) was calculated to evaluate the model performance. RESULTS: After the screening, 10 radiomic features were selected. The AUC and accuracy of the radiomic feature variables random forest model in the testing set were 0.727 (95% CI, 0.694-0.760) and 0.646 (95% CI, 0.620-0.673), respectively. When PSA and radiomic feature variables were included in the random forest model, the AUC and accuracy of the model were 0.770 (95% CI, 0.740-0.800) and 0.713 (95% CI, 0.688-0.738), respectively. While the BLS method was utilized to construct the model, the AUC and accuracy of the model were 0.726 (95% CI, 0.693-0.759) and 0.698 (95% CI, 0.673-0.723), respectively. In predictions for different Gleason grades, the highest AUC of 0.847 (95% CI, 0.749-0.945) was found to predict Gleason grade 5 (Gleason score ≥9). CONCLUSIONS: A model based on transrectal ultrasound image features showed a good ability to predict Gleason scores in prostate cancer patients. ADVANCES IN KNOWLEDGE: This study used ultrasound-based radiomics to predict the Gleason score of patients with prostate cancer.

Exploring the primary magnetic parameters affecting chemical fractions of heavy metal(loid)s in lake sediment through an interpretable workflow.

The magnetic properties of lake sediments account for close relationships with heavy metal(loid)s (HMs), but little is known about their relationships with chemical fractions (CFs) of HMs. Establishing an effective workflow to predict HMs risk among various machine learning (ML) methods in conjunction with magnetic measurement remains challenging. This study evaluated the simulation efficiency of nine ML methods in predicting the risk assessment code (RAC) and ratio of the secondary and primary phases (RSP) of HMs with magnetic parameters in sediment cores of a shallow lake. The sediment cores were collected and sliced, and the total amount and CFs of HMs, as well as magnetic parameters, were determined. Support vector machine (SVM) outperformed other models, as evidenced by coefficient of determination (R2) > 0.8. Interpretable machine learning (IML) methods were employed to identify key indicators of RAC and RSP among the magnetic parameters. Values of χARM, HIRM, χARM/χ, and χARM/SIRM of sediments ranging in 220-500 × 10-8 m3/kg, 30-40 × 10-5Am2/kg, 15-25, and 0.5-1, respectively, indicated the potential ecological risks of Cd, Hg, and Sb. This study offers new perspectives on the risk assessment of HMs in lake sediments by combining magnetic measurement with IML workflow.

PFKFB3 in neovascular eye disease: unraveling mechanisms and exploring therapeutic strategies.

BACKGROUND: Neovascular eye disease is characterized by pathological neovascularization, with clinical manifestations such as intraocular exudation, bleeding, and scar formation, ultimately leading to blindness in millions of individuals worldwide. Pathologic ocular angiogenesis often occurs in common fundus diseases including proliferative diabetic retinopathy (PDR), age-related macular degeneration (AMD), and retinopathy of prematurity (ROP). Anti-vascular endothelial growth factor (VEGF) targets the core pathology of ocular angiogenesis. MAIN BODY: In recent years, therapies targeting metabolism to prevent angiogenesis have also rapidly developed, offering assistance to patients with a poor prognosis while receiving anti-VEGF therapy and reducing the side effects associated with long-term VEGF usage. Phosphofructo-2-kinase/fructose-2,6-bisphosphatase 3 (PFKFB3), a key enzyme in targeted metabolism, has been shown to have great potential, with antiangiogenic effects and multiple protective effects in the treatment of neovascular eye disease. In this review, we summarize the mechanisms of common types of neovascular eye diseases; discuss the protective effect and potential mechanism of targeting PFKFB3, including the related inhibitors of PFKFB3; and look forward to the future exploration directions and therapeutic prospects of PFKFB3 in neovascular eye disease. CONCLUSION: Neovascular eye disease, the most common and severely debilitating retinal disease, is largely incurable, necessitating the exploration of new treatment methods. PFKFB3 has been shown to possess various potential protective mechanisms in treating neovascular eye disease. With the development of several drugs targeting PFKFB3 and their gradual entry into clinical research, targeting PFKFB3-mediated glycolysis has emerged as a promising therapeutic approach for the future of neovascular eye disease.

Comprehensive Analysis of circRNA, lncRNA, miRNA and mRNA Expression Profiles and Their Competing Endogenous RNA Networks in Hepatitis B Virus-Related Hepatocellular Carcinoma.

Pursuing knowledge about circular RNA (circRNA), long non-coding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) expression profiles and their competing endogenous RNA (ceRNA) networks in hepatitis B virus-related hepatocellular carcinoma (HBV-related HCC) was the focus of this research. Expression patterns of circRNAs, lncRNAs, miRNAs, and mRNAs were searched for in relation to HBV-related HCC using whole-transcriptome sequencing. The expression levels of chosen circRNA, lncRNA, miRNA, and mRNA were analyzed using quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The potential connections and roles of ceRNA were deduced via bioinformatics research. The sum of 284 circRNAs, 2,927 lncRNAs, 693 miRNAs, and 5566 mRNAs were discovered to be expressed at considerably different levels in HBV-related HCC tissue and adjacent normal tissue. And the most significantly up- and down-regulated circRNAs, lncRNAs, miRNAs, and mRNAs were verified in HBV-related HCC by qRT-PCR. The circRNA/miRNA/mRNA and lncRNA/miRNA/mRNA networks of HBV-related HCC were established, and the ceRNA regulatory networks revealed the gene expression mechanisms controlled by ncRNAs. Collectively, we revealed the contribution of various circRNA, lncRNA, miRNA, and mRNA expression profiles and identified their ceRNA regulatory networks in HBV-related HCC, providing a theoretical basis for further exploration.

Active Micro-Nano-Collaborative Bioelectronic Device for Advanced Electrophysiological Recording.

The development of precise and sensitive electrophysiological recording platforms holds the utmost importance for research in the fields of cardiology and neuroscience. In recent years, active micro/nano-bioelectronic devices have undergone significant advancements, thereby facilitating the study of electrophysiology. The distinctive configuration and exceptional functionality of these active micro-nano-collaborative bioelectronic devices offer the potential for the recording of high-fidelity action potential signals on a large scale. In this paper, we review three-dimensional active nano-transistors and planar active micro-transistors in terms of their applications in electro-excitable cells, focusing on the evaluation of the effects of active micro/nano-bioelectronic devices on electrophysiological signals. Looking forward to the possibilities, challenges, and wide prospects of active micro-nano-devices, we expect to advance their progress to satisfy the demands of theoretical investigations and medical implementations within the domains of cardiology and neuroscience research.

Coactivation of Hydrogen Peroxide Using Pyrogenic Carbon and Magnetite for Sustainable Oxidation of Organic Pollutants.

Pyrogenic carbon and magnetite (Fe3O4) were mixed together for the activation of hydrogen peroxide (H2O2), aiming to enhance the oxidation of refractory pollutants in a sustainable way. The experimental results indicated that the straw-derived carbon obtained by pyrolysis at 500-800 °C was efficient on coactivation of H2O2, and the most efficient one was that prepared at 700 °C (C700) featured with abundant defects. Specifically, the reaction rate constant (kobs) for removal of an antibiotic ciprofloxacin in the coactivation system (C700/Fe3O4/H2O2) is 12.5 times that in the magnetite-catalyzed system (Fe3O4/H2O2). The faster pollutant oxidation is attributed to the sustainable production of •OH in the coactivation process, in which the carbon facilitated decomposition of H2O2 and regeneration of Fe(II). Besides the enhanced H2O2 utilization in the coactivation process, the leaching of iron was controlled within the concentration limit in drinking water (0.3 mg·L-1) set by the World Health Organization.

Innovative explorations: unveiling the potential of organoids for investigating environmental pollutant exposure.

As the economy rapidly develops, chemicals are widely produced and used. This has exacerbated the problems associated with environmental pollution, raising the need for efficient toxicological evaluation techniques to investigate the toxic effects and mechanisms of toxicity of environmental pollutants. The progress in the techniques of cell culture in three dimensions has resulted in the creation of models that are more relevant in terms of biology and physiology. This enables researchers to study organ development, toxicology, and drug screening. Adult stem cells (ASCs) and induced pluripotent stem cells (iPSCs) can be obtained from various mammalian tissues, including cancerous and healthy tissues. Such stem cells exhibit a significant level of tissue memory and ability to self-assemble. When cultivated in 3D in vitro environments, the resulting organoids demonstrate a remarkable capacity to recapitulate the cellular composition and function of organs in vivo. Recently, many tumors' tissue-derived organoids have been widely used in research on tumor pathogenesis, drug development, precision medicine, and other fields, including those derived from colon cancer, cholangiocarcinoma, liver cancer, and gastric cancer. However, the application of organoid models for evaluating the toxicity of environmental pollutants is still in its infancy. This review introduces the characteristics of the toxicity responses of organoid models upon exposure to pollutants from the perspectives of organoid characteristics, tissue types, and their applications in toxicology; discusses the feasibility of using organoid models in evaluating the toxicity of pollutants; and provides a reference for future toxicological studies on environmental pollutants based on organoid models.

Inflammatory response in mouse lungs to haze episodes under different backgrounds of particulate matter exposure.

Particulate matter (PM) toxicity has mostly been investigated through in vitro exposure or tracheal infusion in animal models. However, given the complexity of ambient conditions, most animal studies do not mimic real-life PM exposure. In this work, we established a novel integrated exposure model to study the dynamic inflammatory response and defense strategies in ambient PM-exposed mice. Three groups of male C57BL/6 mice were kept in three chambers with pre-exposure to filtered air (FA), unfiltered air (UFA), or the air with a low PM concentration (PM2.5 ≤ 75 µg/m3) (LPM), respectively, for 37 days. Then all three groups of mice were exposed to haze challenge for 3 days, followed by exposure in filtered air for 7 days to allow recovery. Our results suggest that following a haze challenge, the defense strategies of mice of filtered air (FA) and low PM (LPM) groups comprised a form of "counterattack", whereas the response of the unfiltered air (UFA) group could be viewed as a "silence". While the latter strategy protected the lung tissues of mice from acute inflammatory damage, it also foreshadowed the development of chronic inflammatory diseases. These findings contribute to explaining previously documented PM-associated pathogenic mechanisms.

Ventral Tegmental Area Glutamatergic Neurons Facilitated Emergence From Isoflurane Anesthesia Involves Excitation of Lateral Septum γ-Aminobutyric Acid-ergic Neurons in Mice.

BACKGROUND: Ventral tegmental area (VTA) glutamatergic neurons promote wakefulness in the sleep-wake cycle; however, their roles and neural circuit mechanisms during isoflurane (ISO) anesthesia remain unclear. METHODS: Fiber photometry and in vivo electrophysiology were used to observe the changes in neuronal or terminal activity during ISO anesthesia and arousal processes. Optogenetic and anesthesia behaviors were used to investigate the effects of VTA glutamatergic neurons and their projections to the lateral septum (LS) during ISO anesthesia and arousal. Anterograde and retrograde tracings were performed to identify the connections between VTA glutamatergic neurons and the LS. RESULTS: Population activity and firing rates of VTA glutamatergic neurons decreased during ISO anesthesia (ISO: 95% confidence interval [CI], 0.83-2.06 Spikes.s-1 vs wake: 95% CI, 3.53-7.83 Spikes.s-1; P =.0001; n = 34 from 4 mice). Optogenetic activation of VTA glutamatergic neurons reduced the burst-suppression ratio in electroencephalography (laser: 95% CI, 13.09%-28.76% vs pre: 95% CI, 52.85%-71.59%; P =.0009; n = 6) and facilitated emergence (ChR2: 95% CI, 343.3-388.0 seconds vs mCherry: 95% CI, 447.6-509.8 seconds; P < .0001; n = 11/12) from ISO anesthesia. VTA glutamatergic neurons monosynaptically innervated LS γ-aminobutyric acid (GABA)-ergic neurons. The activity of VTA glutamatergic terminals in the LS decreased during ISO anesthesia, and optogenetic activation of the VTA glutamatergic terminals in the LS facilitated emergence from ISO anesthesia. Furthermore, optogenetic activation of VTA glutamatergic terminals increased the firing rates of LS γ-aminobutyric acid-ergic (GABAergic) neurons (laser: 95% CI, 0.85-4.03 Spikes.s-1 vs pre: 95% CI, 0.24-0.78 Spikes.s-1; P =.008; n = 23 from 4 mice) during ISO anesthesia. CONCLUSIONS: VTA glutamatergic neurons facilitated emergence from ISO anesthesia involving excitation of LS GABAergic neurons.

The Effectiveness of a Community Nurse-Led Support Program for Dementia Caregivers in Chinese Communities: The Chongqing Ageing and Dementia Study.

Background: As the primary caregivers for people with dementia in China, family caregivers face a significant care burden that can negatively impact their mental and physical health. It is vital to investigate ways to support these caregivers. Objective: To assess the effectiveness of a program led by community nurses to support caregivers of individuals with dementia. Methods: A total of 30 caregivers received nurse-led support in addition to usual care, while 28 caregivers received only usual care. The primary outcome was caregivers' sense of competency in providing dementia care, which was measured using the Short Sense of Competence Questionnaire (SSCQ). Secondary outcomes included caregivers' ability to perform daily activities, behavioral and psychological symptoms of dementia (BPSD) using a neuropsychiatric inventory questionnaire, and quality of life using the short form health survey (SF-36). The trial was registered at the Chinese Clinical Trial Registry (ChiCTR 2300071484). Results: Compared to the control group, the intervention group had significantly higher SSCQ scores and a lower caregiver distress index over time. Physical and mental health-related quality of life also improved significantly among caregivers in the intervention group. However, there was no significant difference between the two groups in terms of activities of daily living and BPSD. Conclusions: The community nurse-led support program significantly improved caregivers' competency in providing dementia care and quality of life and reduced distress. These findings have important implications for dementia care policies, resources, and workforce development in China, including strengthening community dementia care services through collaboration with specialists in hospitals.

Gas-particle partitioning of organophosphate esters in indoor and outdoor air and its implications for individual exposure.

The extensive utilization of organophosphate esters (OPEs) has resulted in their widespread presence in the environment, raising concerns about potential human health risks. In this study, 13 OPEs were analyzed in both gas and particle phases as well as in indoor and outdoor atmospheric environments. Moreover, human exposure to OPEs were investigated within a university environment, focusing on forehead contact and individual PM2.5 inhalation. The results showed similar distribution patterns of OPEs indoors and outdoors, although higher concentrations were found indoors. The average atmospheric concentration of ∑OPEs (combining particle and gaseous OPEs) was 1575 pg/m3 in the outdoor environment and 6574 pg/m3 ∑OPEs in the indoor microenvironments. The overwhelming majority of OPEs exhibit a pronounced propensity to adsorb onto PM2.5 particles. Notably, the concentration of OPEs on the forehead differed significantly from that in the atmospheric environment, whereas individual PM2.5 exposure was consistent with the concentration of indoor PM2.5. Intriguingly, some OPEs with high octanol-water partition coefficient (log Kow) were not detected in the environment but found on human foreheads. Gas-particle partitioning was predicted using the Harner-Bidleman and Li-Ma-Yang models and the results were in agreement with the monitoring data for approximately half of the OPE monomers. Correlations between OPEs exposure and gas-particle partitioning were found to be more significant for novel OPEs. No non-cancer risk to humans through individual exposure to OPEs was identified via forehead exposure or inhalation. The previously unreported relationship between individual exposure and the environmental occurrence of traditional and novel OPEs demonstrated in this study highlights the importance of evaluating the potential health risks associated with actual OPE exposure.

Time series prediction of the chemical components of PM2.5 based on a deep learning model.

Modeling-based prediction methods enable rapid, reagent-free air pollution detection based on inexpensive multi-source data than traditional chemical reaction-based detection methods in order to quickly understand the air pollution situation. In this study, a convolutional neural network (CNN) and long and short-term memory (LSTM) neural networks are integrated to create a CNN-LSTM time series prediction model to predict the concentration of PM2.5 and its chemical components (i.e., heavy metals, carbon component, and water-soluble ions) using meteorological data and air pollutants (PM2.5, SO2, NO2, CO, and O3). In the integrated CNN-LSTM model, the CNN uses convolutional and pooling layers to extract features from the data, whereas the powerful nonlinear mapping and learning capabilities of LSTM enable the time series prediction of air pollution. The experimental results showed that the CNN-LSTM exhibited good generalization ability in the prediction of As, Cd, Cr, Cu, Ni, and Zn, with a mean R2 above 0.9. Mean R2 predicted for PM2.5, Pb, Ti, EC, OC, SO42-, and NO3- ranged from 0.85 to 0.9. Shapley value showed that PM2.5, NO2, SO2, and CO had a greater influence on the predicted heavy metal results of the model. Regarding water-soluble ions, the predicted results were dominantly influenced by PM2.5, CO, and humidity. The prediction of the carbon fraction was affected mainly by the PM2.5 concentration. Additionally, several input variables for various components were eliminated without affecting the prediction accuracy of the model, with R2 between 0.70 and 0.84, thereby maximizing modeling efficiency and lowering operational costs. The fully trained model prediction results showed that most predicted components of PM2.5 were lower during January to March 2020 than those in 2018 and 2019. This study provides insight into improving the accuracy of modeling-based detection methods and promotes the development of integrated air pollution monitoring toward a more sustainable direction.

N,S-codoped biochar outperformed N-doped biochar on co-activation of H2O2 with trace dissolved Fe(â ¢) for enhanced oxidation of organic pollutants.

Co-activation of H2O2 with biochar and iron sources together provides an attractive strategy for efficient removal of refractory pollutants, because it can solve the problems of slow Fe(Ⅱ) regeneration in Fenton/Fenton-like processes and of low •OH yield in biochar-activated process. In this study, a wood-derived biochar (WB) was modified by heteroatom doping for the objective of enhancing its reactivity toward co-activation of H2O2. The performance of the co-activated system using doped biochars and trace dissolved Fe(Ⅲ) on oxidation of organic pollutants was evaluated for the first time. The characterizations using X-ray photoelectron spectroscopy (XPS), Raman spectra and electrochemical analyses indicate that heteroatom doping introduced more defects in biochar and improved its electron transfer capacity. The oxidation experiments show that heteroatom doping improved the performance of biochar in the co-activated process, in which the N,S-codoped biochar (NSB) outperformed the N-doped biochar (NB) on oxidation of pollutants. The reaction rate constant (kobs) for oxidation of sulfadiazine in NSB + Fe + H2O2 is 2.25 times that in NB + Fe + H2O2, and is 72.9 times that in the Fenton-like process without biochar, respectively. The mechanism investigations indicate that heteroatom doping enhanced biochar's reactivity on catalyzing the decomposition of H2O2 and on reduction of Fe(Ⅲ) due to the improved electron transfer/donation capacity. In comparison with N-doping, N,S-codoping provided additional electron donor (thiophenic C-S-C) for faster regeneration of Fe(Ⅱ) with less amount of doping reagent used. Furthermore, co-activation with NSB maintained to be efficient at a milder acidic pH than Fenton/Fenton-like processes, and can be used for oxidation of different pollutants and in real water. Therefore, this research provides a novel, sustainable and cost-efficient method for oxidation of refractory pollutants.

Increased Platelet Distribution Width Predicts 3-Year Recurrence in Patients with Hepatocellular Carcinoma After Surgical Resection.

Background: Platelet distribution width (PDW) is a marker of platelet anisocytosis that increases with platelet activation. The clinical implications of PDW in HCC are not well-defined. This study aimed to determine whether PDW could predict recurrence in patients with HCC after resection. Methods: Between January and December 2008, 471 patients with HCC were recruited retrospectively. The clinicopathological characteristics of patients with HCC were analyzed based on the relationship between the two PDW groups. Kaplan-Meier curves and multivariate Cox regression analyses were used to evaluate the relationship between PDW and disease-free survival (DFS). A novel nomogram was developed based on the identified independent risk factors. Its accuracy was evaluated using a calibration curve and concordance index. The predictive value was evaluated using a receiver operating characteristic (ROC) curve. Results: PDW was significantly associated with direct bilirubin, total bilirubin, urea, and prothrombin time. Patients with PDW ≥ 17.1 were a significantly shorter DFS than those with PDW < 17.1 (17.98% vs 49.83%, p< 0.001). Multivariate analysis determined that alpha-fetoprotein (AFP), carcinoembryonic antigen, microvascular invasion (MVI), tumor size, and tumor number were the independent variables associated with DFS. Patients with PDW ≥ 17.1 had a hazard ratio of 1.381 (95% confidence interval: 1.069-1.783, p = 0.014) for DFS. AFP, PDW, MVI, tumor size, and tumor number were identified as preoperative independent risk factors for DFS and used to establish the nomogram. Calibration curve analysis revealed that the standard curve fitted well with the predicted curve. ROC curve analysis demonstrated the high efficiency of the nomogram. Conclusion: Increased PDW may predict recurrence-free survival in patients with HCC. Our nomogram model also performed well in predicting patient prognoses.

Prediction of atmospheric pollutants in urban environment based on coupled deep learning model and sensitivity analysis.

Accurate and efficient predictions of pollutants in the atmosphere provide a reliable basis for the scientific management of atmospheric pollution. This study develops a model that combines an attention mechanism, convolutional neural network (CNN), and long short-term memory (LSTM) unit to predict the O3 and PM2.5 levels in the atmosphere, as well as an air quality index (AQI). The prediction results given by the proposed model are compared with those from CNN-LSTM and LSTM models as well as random forest and support vector regression models. The proposed model achieves a correlation coefficient between the predicted and observed values of more than 0.90, outperforming the other four models. The model errors are also consistently lower when using the proposed approach. Sobol-based sensitivity analysis is applied to identify the variables that make the greatest contribution to the model prediction results. Taking the COVID-19 outbreak as the time boundary, we find some homology in the interactions among the pollutants and meteorological factors in the atmosphere during different periods. Solar irradiance is the most important factor for O3, CO is the most important factor for PM2.5, and particulate matter has the most significant effect on AQI. The key influencing factors are the same over the whole phase and before the COVID-19 outbreak, indicating that the impact of COVID-19 restrictions on AQI gradually stabilized. Removing variables that contribute the least to the prediction results without affecting the model prediction performance improves the modeling efficiency and reduces the computational costs.